http://jaymargalus.com/Ghost 0.5Tue, 03 Mar 2015 22:31:30 GMT60Over the past several weeks, I've been winding down client work that I've accumulated during my days as a contractor in preparation to go to work for a big data company based out of San Jose (don't worry, I'll still be living in Mokena and working out of SpaceLab!). More on the new opportunity later.

But the point is that, because of the wind-down, I've had a lot of time on my hands to work on various projects that I dream up. One of the more ambitious ones was an idea that came to me two weeks ago: I'd build a dining room table for my wife for Christmas.

As you can imagine, a two-week window is a pretty tight schedule for a table. I had to buy the lumber, assemble the table, sand it, stain it, cure it, and allow it to dry in that short bit of time.

The design I ended up going with for the table was a farmhouse-style build that I modified from a schematic found on Ana White. Post-build, the table ended up being 45" wide by 88" long, built in white pine and cedar sourced from a local hardware store. The table is stained in cherry to match the maple cherry floors that I put in when we first got the house.

Needless to say I finished the table with a few days to spare, and now have pictures to prove it! Without further ado:

Homebrewers, craft brewers, and even larger brewers have all run into this question one time or another. There are, of course, your mainstays: Pumpkin Ale and Octoberfest for October, Winter Ales and Porters for the winter, Hefeweisen for summer, and so on. The selection of beers at your typical store changes based on the season all the time. This is what we call normal data; stuff we already know.

But what other beers are consumers looking for? What're people drinking that we don't know about, and when are they drinking it? What don't we know?

Those are the questions I attempted to (at least start to) answer in a recent analysis of a dataset including over 1.5 million beer reviews, over 400,000 contributors, and 12 (2000-2012) years of data.

Beer as Big Business

Craft beer, and craft breweries, are a growing industry that deserve more analysis. Almost 200 million barrels (bbls), or six billion gallons of beer, were sold in 2013. Of that, over 15 million barrels, or nearly 500 million gallons, were craft beer. $100 billion dollars was made on beer last year, and of that, $14.3 billion was spent on craft beers. This is a 17.2% increase in craft beer sales from 2012-2013.1

Craft beer is now big business, and because of that growth, larger breweries are getting into the game, too. Yet despite all the growth and buzz surrounding craft beer, it's still a relatively nascient market. So when we ask questions like "what beer should we brew?" the answers aren't always available.

This is a solveable problem.

There's tons of great beer data already out there, often going back over a decade. Untappd has an API to access their data, for instance. Additionally, Twitter and Facebook are treasure-troves of people posting what they're drinking almost religiously. Even review sites like Beer Advocate have, from time-to-time, opened up their data. We can, then, collect that data and analyze it using typical visualization and insight methodologies. From there, we can infer what beers we should brew.

So, with a few caveats, I present my first small crack at the data heap I've got at my fingertips. At its core, the visualizations below represent a way to see what beers styles and brands are popular in any given season.

Notes:

Things like IPAs and Pale Ales have been filtered out of the bubble graph because, frankly, they pollute the data (they're constantly popular -- come on, people). However, you can still find IPA data in the lower graph.

By hovering over the bar graph in the top right corner, you can see what beer brands are being reviewed frequently. Some of this data was also normalized to provide a level of accuracy.

I'll be updating this page over the coming weeks. Probably with some more complex D3 visualizations. In the process, I'll be adding the following: word clouds for flavor profiles, Twitter and Untappd data visualizations, regionalized visualizations, more normalized data, aggregated data combined with beer ratings, and sentiment analyses of beer brands and types.

Given those caveats, I still believe this data is an interesting start and gives us all something to think about. Enjoy:

]]>http://jaymargalus.com/beer-data/e44cbade-6e73-42de-8021-461366a2cafcThu, 06 Nov 2014 04:30:27 GMTMy old hackerspace Workshop 88 was recently commissioned by MapR to develop custom conference badges -- wearable technology -- for the Big Data Conference. The objective was to use that wearable technology, combined with MapR tech, to showcase the data being collected by the badges and transform it into an interesting experience.

In the last week or so of the project I was called in to help polish the game experience, create the web and data servers, and design the web visualizations through a combination of MapR tech, Apache Drill, Nodejs, and D3. Along the way we ended up redesigning most of the original experiential concept.

The badges had initially been designed to collect data and simply use it to dictate achievements. The idea was to use sensors to detect UV and IR exposure, eposure to other attendee badges, times of certain actions logged, and more, then upload it to a central server. From there, arbitrary achievements could be designed around them.

Coming from a game design background, this didn't seem entirely compelling to me. The badge designs were great, but the experience coming out of them was still lacking. Achievements are not core to any good interactive experience, and people would likely lose interest in the arbitrary data quickly. So I started to brainstorm ways to use the data we were receiving from the badges into something more compelling.

One of the best ways...

to think about interactive design experience is to look at it as a balance between certainty and uncertainty. Too much uncertainty, and a game is too random. Too little, and it's on rails.

When looking at the data coming in from the badges, the question became: how can we take a complete picture of information like the stuff we were gathering and use it to introduce uncertainty into the game? Another question was: how can we craft an experience by displaying the information in such a way as to allow attendees to make meaningful decisions? This is often referred to as insights in the big data world.

Taking a cue from games like Werewolf and Pandemic, I wound up arriving at a few conclusions about the badges:

The game needed more game-like elements. Seems like a simple conclusion to arrive at, but it isn't always very obvious. Things like obstacles, negative and positive feedback loops, and player choice needed to be introduced.

The data that we were collecting needed to be used to create further uncertainty in the game. We would need to introduce an anomaly (in this case, a virus) into the game in order to generate that uncertainty.

An online interface that provided up-to-date information would be necessary for immediate feedback. With in-person games like this (often referred to as augmented reality games), providing players with feedback is key. This is the insights portion of the game.

Over the past couple days, I believe we've addressed many of these problems. The end result is the Big Data Outbreak project: a virus outbreak-like experience that simulates the spread of disease within a population. By using a form of near field communication to allow the badges to talk to each other, and in turn the server (through the use of RPi kiosks), badges communicate the disease between themselves, and the outbreak spreads. As the outbreak spreads, people are forced to look for a way to heal themselves (using the kiosks), or perish.

In practice, we've created a real life simulation of an epidemic using only conference badges.

I'm quite excited -- and nervous -- to see how these badges turn out in the coming days. With the short development cycle for this game, we've been unable to playtest it to any meaningful extent. Yet there's something about the potential of the information we're collecting, and, I think, something about wearable technology that shows a lot of promise for augmented reality games. The true interaction between technology and the real world opens up many possibilities.

]]>http://jaymargalus.com/big-data-outbreak/34c12d38-e7a8-4cb0-bbd9-ced02872bcf1Tue, 30 Sep 2014 07:46:38 GMTI've been known to run a podcast from time to time, and may even do one again in the future. In the past 3 years, I've collaborated with two really talented people on two different podcasts: George Hufnagl on MyGiant Podcast, and David Wolinsky on DIY Gamedev.

Unfortunately, both of those websites are defunct now. Our musings, until now, deleted from the internet.

Fortunately, I've archived everything on Amazon S3. Here are the episodes, for posterity:

If you have a Mac, want access to some fantastic software, and don't have $1,000 kicking around, then the Rhinoceros Mac beta is for you. It's totally free, assumedly while the beta goes on. Normal pricetag for this is over $1,000.

Printing, particularly lettering, works best at around a 2" or greater build volume. At least on the Da Vinci, at 100 microns, decent print resolution works in that range.

If you're unsure if the size of your designed object will work, print it out on paper at scale first, then cut it out to get a really good visualization.

I'd never published something to Thingiverse before, but as of a day online, my design has already received several downloads and likes. This seems to be a great way to share designs and get noticed.

If you'd like to check out the keychain design, and any of my future objects, head on over to my Thingiverse profile.

]]>http://jaymargalus.com/my-thingiverse-profile/913e47fd-073c-4df5-bf7e-c49707fd0707Mon, 25 Aug 2014 19:20:23 GMTA few months ago in our Chicago gamedev Fantasy Football League, someone posted a video of kids digging around in sand. Except, that's not all that was happening. The sand changed as they dug, projecting mountains, flowing rivers, grass, and even volcanoes complete with gushing lava on top of the surface.

I had to make one. Think of the possibilities!

A couple days later, I had a sketch of the sandbox. It needed to be built at a 4:3 aspect ratio, and being that projectors and hardware aren't quite up to tolerating a 4 yard by 3 yard box, I decided to go for a simple 4' x 3' sandbox, elevated about 30" off the ground. Here's the original sandbox design:

After that, I began building the box that would drive the system. We had an older (but really well equipped) PC laying around that I reformatted and put Linux (Ubuntu) on. Then I loadedthesoftware required to get the project to run, and ran some tests.

Impatient to get this thing off the road, I skipped further calibration steps in order to verify it worked. Okay, I just wanted to play with it. But more importantly, the kids at SpaceLab that day wanted to play with it. Here's the result:

That's it for now. My next plans are to figure out how to reinterpret the sandbox data back onto the computer, then use that to mirror what's happening on the sand in Minecraft. Basically, create a physical way to manipulate the game.

Sound fun? Follow the progress of this project, and other projects of mine, by subscribing to my blog.

]]>http://jaymargalus.com/the-augmented-reality-sandbox/0825decc-acb7-42f7-889a-b796c27b0e70Sun, 24 Aug 2014 02:44:53 GMTOn September 13, 2014, with the help of many other SpaceLab members, makers, sponsors, community members, and volunteers, I'll be hosting my very first Mokena Mini Maker Faire. This has been a dream of mine, really, over the past the five years I've been involved in hackerspaces. Hosting a Maker Faire is an excellent way to alter how we look at the world; to educate others and expand their minds, a passion of my own.

David Foster Wallace's commencement speech at Kenyon College, famously entitled "This is Water" is well enough known now to sum it up shortly: it's easy to get stuck in a way of thinking, on rails, in life. A good education, or a person who's trained themselves to objectively think, serves us well inasmuch as they're able to break out of our every day commonplace thought patterns.

Maker Faires help us do exactly that: they help us see things differently.

This year's Mokena Mini Maker Faire will host a trebuchet, a near space balloon, a 10 ft. tall musical instrument, a Borg boquet, an augmented reality sandbox, learn-to-solder tent, green screen lightsaber battles, an Etsy craft table, and more. The collective brainpower and artistic expression shown in just these exhibits is incredibly exciting, and is exactly the mix of science, technology, and art that encourages different thinking, and breaks us out of our collective ruts.